Data analytics for diagnosis and prediction of central line-associated bloodstream infections in critical care units

Abstract

Central line-associated bloodstream infections (CLABSI) are among leading causes of in-hospital deaths in the US and are a significant factor for increased morbidity, mortality and health care costs. This study examined significant attributes for CLABSI positive cases within intensive care units to develop a CLABSI hazard rate and risk score.

Description

45th Biennial Convention 2019 Theme: Connect. Collaborate. Catalyze.

Authors

Mary A. Hooshmand
Ramin Moghaddass
Christine Toledo
Erotokritos Skordilis

Author Details

Mary A. Hooshmand, PhD, MS, BS, RN; Christine Toledo, BSN -- School of Nursing and Health Studies, University of Miami, Coral Gables, Florida, USA; Ramin Moghaddass, PhD, Department of Industrial Engineering, University of Miami, College of Engineering, Coral Gables, Florida, USA; Erotokritos Skordilis, BS, College of Engineering, Department of Industrial Engineering, University of Miami, Coral Gables, Florida, USA

Sigma Membership

Non-member

Lead Author Affiliation

University of Miami, Coral Gables, Florida, USA

Type

Presentation

Format Type

Text-based Document

Study Design/Type

N/A

Research Approach

N/A

Keywords:

Central Line Associated Bloodstream Infections (CLABSI), Data Analytics, Early Warning Systems

Recommended Citation

Hooshmand, Mary A.; Moghaddass, Ramin; Toledo, Christine; and Skordilis, Erotokritos, "Data analytics for diagnosis and prediction of central line-associated bloodstream infections in critical care units" (2019). Convention. 43.
https://www.sigmarepository.org/convention/2019/presentations_2019/43

Conference Name

45th Biennial Convention

Conference Host

Sigma Theta Tau International

Conference Location

Washington, DC, USA

Conference Year

2019

Rights Holder

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Acquisition

Proxy-submission